projectLSA

projectLSA is an R package that provides a complete graphical user interface (GUI) for conducting Latent Structure Analysis (LSA) through a Shiny application. It integrates multiple latent variable methods, including:

• Latent Profile Analysis (LPA)
• Latent Class Analysis (LCA)
• Latent Trait Analysis (LTA / IRT)
• Exploratory Factor Analysis (EFA)
• Confirmatory Factor Analysis (CFA)

All analyses can be performed without writing any code, making the package accessible for researchers, students, and applied analysts.

Installation

# Install from CRAN (when available)
install.packages("projectLSA")

# Install development version from GitHub (optional)
# remotes::install_github("hasandjidu/projectLSA")

Launch the Application

library(projectLSA)
run_projectLSA()

This opens the full Shiny application, including all LSA modules, data upload, built-in datasets, interactive plots, and reporting features.

Features

✔ Latent Profile Analysis (LPA)

• Upload your own dataset or use built-in examples.
• Fit multiple LPA models automatically.
• Compare AIC, BIC, entropy, and class size.
• Visualize the best model with customizable class names.

✔ Latent Class Analysis (LCA)

• Supports categorical indicators.
• Fits multiple class solutions.
• Interactive plots with ggiraph.
• Probability tables and class membership export.

✔ Latent Trait Analysis (LTA / IRT)

• Supports dichotomous and polytomous items.
• Automatically fits Rasch, 2PL, 3PL (or PCM/GRM/GPCM).
• ICC plots, test information, factor scores.
• Multi-dimensional visualization with 3D surfaces and heatmaps.

✔ Exploratory Factor Analysis (EFA)

• KMO, Bartlett test, parallel analysis.
• Factor extraction with rotation.
• Factor scores and loading matrix export.
• Clean HTML summaries for clearer interpretation.

✔ Confirmatory Factor Analysis (CFA)

• Lavaan model editor.
• Fit measures, loadings, factor scores.
• Fully customized SEM path diagrams.

Example Screenshots

LPA (Latent Profile Analysis)

LCA (Latent Class Analysis)

### CFA (Confirmatory Factor Analysis) ### SEM (Structural Equation Modelling)

LTA (Latent Trait Analysis/ IRT)

Citation

If you use projectLSA in publications, please cite:

Djidu, H., Retnawati, H., Hadi, S., & Haryanto (2026). projectLSA:R Shiny application for latent structure analysis with a graphical user interface. https://doi.org/10.32614/CRAN.package.projectLSA

Contributing

Bug reports and feature requests are welcome:

https://github.com/hasandjidu/projectLSA/issues

License

MIT License © 2026 Hasan Djidu